Interactive Visual Construction of Financial Compositing Indicators



In the financial domain, trend analysis is an important tool to predict financial developments. For this prediction, different indicators, such as macro-economic factors, statistical metrics and technical indicators like volatility of the target market price, are analyzed. Usually, a single indicator cannot capture the financial development reliably, so analysts look at multiple indicators. A common way to do this is to combine multiple independent indicators in so-called composite indicators.

However, the construction and validation of these composite indicators is an open challenge. Usually, analysts follow elaborate guidelines, such as provided by the OECD [1,2]. These guidelines comprise a lot of steps, and performing these steps without a dedicated tool is tedious and can lead to arbitrary and unstable compound indicators.




In this project, an existing financial dashboard system (see screenshot figure) should be extended to facilitate the step-wise construction and validation of compound indicators to predict a given reference curve. Following the OECD guidelines [1], financial analysts should be provided with different common options to compare, normalize, filter, and shift indicator curves. For every step, uncertainty visualization should be used to indicate the reliability of the current state of the compound indicator. Finally, a comparative visualization should facilitate the selection of candidate compound indicators.


  • Strong interest in statistics and information visualization.
  • Experience in web programming, in particular JavaScript.
  • Experience with web technologies, like Node.js, Angular.js, or d3.js, advantageous.
  • Commitment to a tight collaboration with domain experts from the financial domain.
  • Knowledge in the financial domain is not required, but the student should be interested in the topic.


The project will be built upon an existing online financial dashboard system, using Node.js, Angular.js, d3.js, and Reactive.js. Live financial data is pulled from economic databases.

The work will be done in tight collaboration with an IT-company focusing on financial trend analysis (PS Quant: . In case of a successful completion of the project, there will be a monetary reward.


For more information please contact Michael PĆ¼hringer or Manuela Waldner (